Functional Parametric Elasto-Dynamics for Efficient Multicomponent Design
In industrial settings, engineering products are often divided into separate components for detailed conception. They often require iterative corrections between different designers/teams to optimize the final product with all components assembled into a system. This article proposes a surrogate mod...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-12-01
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| Series: | Computation |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2079-3197/10/12/218 |
| _version_ | 1797460812702416896 |
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| author | Jiajun Wu Chady Ghnatios Philippe Mordillat Yves Tourbier Francisco Chinesta |
| author_facet | Jiajun Wu Chady Ghnatios Philippe Mordillat Yves Tourbier Francisco Chinesta |
| author_sort | Jiajun Wu |
| collection | DOAJ |
| description | In industrial settings, engineering products are often divided into separate components for detailed conception. They often require iterative corrections between different designers/teams to optimize the final product with all components assembled into a system. This article proposes a surrogate modeling approach with functional descriptions of parts in the model and aims to accelerate the design and optimization phase in real projects. The approach is applied to a vibration problem of a two-component plate structure, where the model estimates the dynamic behavior of the assembled system when only the properties of each individual part are available. A database is built using high-fidelity numerical simulations, and neural-network-based regressions provide reliable predictions on unseen data. |
| first_indexed | 2024-03-09T17:10:24Z |
| format | Article |
| id | doaj.art-838d81f3bdd147d3a5e52ab1b1a75fcc |
| institution | Directory Open Access Journal |
| issn | 2079-3197 |
| language | English |
| last_indexed | 2024-03-09T17:10:24Z |
| publishDate | 2022-12-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Computation |
| spelling | doaj.art-838d81f3bdd147d3a5e52ab1b1a75fcc2023-11-24T14:07:11ZengMDPI AGComputation2079-31972022-12-01101221810.3390/computation10120218Functional Parametric Elasto-Dynamics for Efficient Multicomponent DesignJiajun Wu0Chady Ghnatios1Philippe Mordillat2Yves Tourbier3Francisco Chinesta4PIMM Laboratory, Arts et Métiers Institute of Technology, CNRS, Cnam, HESAM Université, 151 Boulevard de l’Hôpital, 75013 Paris, FrancePIMM Laboratory, Arts et Métiers Institute of Technology, CNRS, Cnam, HESAM Université, 151 Boulevard de l’Hôpital, 75013 Paris, FranceRenault SAS, 1 Avenue du Golf, 78280 Guyancourt, FranceRenault SAS, 1 Avenue du Golf, 78280 Guyancourt, FrancePIMM Laboratory, Arts et Métiers Institute of Technology, CNRS, Cnam, HESAM Université, 151 Boulevard de l’Hôpital, 75013 Paris, FranceIn industrial settings, engineering products are often divided into separate components for detailed conception. They often require iterative corrections between different designers/teams to optimize the final product with all components assembled into a system. This article proposes a surrogate modeling approach with functional descriptions of parts in the model and aims to accelerate the design and optimization phase in real projects. The approach is applied to a vibration problem of a two-component plate structure, where the model estimates the dynamic behavior of the assembled system when only the properties of each individual part are available. A database is built using high-fidelity numerical simulations, and neural-network-based regressions provide reliable predictions on unseen data.https://www.mdpi.com/2079-3197/10/12/218machine learningartificial intelligencedata-driven modelingelasto-dynamics |
| spellingShingle | Jiajun Wu Chady Ghnatios Philippe Mordillat Yves Tourbier Francisco Chinesta Functional Parametric Elasto-Dynamics for Efficient Multicomponent Design Computation machine learning artificial intelligence data-driven modeling elasto-dynamics |
| title | Functional Parametric Elasto-Dynamics for Efficient Multicomponent Design |
| title_full | Functional Parametric Elasto-Dynamics for Efficient Multicomponent Design |
| title_fullStr | Functional Parametric Elasto-Dynamics for Efficient Multicomponent Design |
| title_full_unstemmed | Functional Parametric Elasto-Dynamics for Efficient Multicomponent Design |
| title_short | Functional Parametric Elasto-Dynamics for Efficient Multicomponent Design |
| title_sort | functional parametric elasto dynamics for efficient multicomponent design |
| topic | machine learning artificial intelligence data-driven modeling elasto-dynamics |
| url | https://www.mdpi.com/2079-3197/10/12/218 |
| work_keys_str_mv | AT jiajunwu functionalparametricelastodynamicsforefficientmulticomponentdesign AT chadyghnatios functionalparametricelastodynamicsforefficientmulticomponentdesign AT philippemordillat functionalparametricelastodynamicsforefficientmulticomponentdesign AT yvestourbier functionalparametricelastodynamicsforefficientmulticomponentdesign AT franciscochinesta functionalparametricelastodynamicsforefficientmulticomponentdesign |